/// <summary>
/// Compute the output for a given input to the neural network. This method
/// provides a parameter to specify an output holder to use. This holder
/// allows propagation training to track the output from each layer.
/// If you do not need this holder pass null, or use the other
/// compare method.
/// </summary>
/// <param name="input">The input provide to the neural network.</param>
/// <param name="useHolder">Allows a holder to be specified, this allows
/// propagation training to check the output of each layer.</param>
/// <returns>The results from the output neurons.</returns>
public virtual INeuralData Compute(INeuralData input,
NeuralOutputHolder useHolder)
{
try
{
return(logic.Compute(input, useHolder));
}
catch (IndexOutOfRangeException ex)
{
throw new NeuralNetworkError(
"Index exception: there was likely a mismatch between layer sizes, or the size of the input presented to the network.",
ex);
}
}
/// <summary>
/// Compute the output for a given input to the neural network. This method
/// provides a parameter to specify an output holder to use. This holder
/// allows propagation training to track the output from each layer.
/// If you do not need this holder pass null, or use the other
/// compare method.
/// </summary>
/// <param name="input">The input provide to the neural network.</param>
/// <param name="useHolder">Allows a holder to be specified, this allows
/// propagation training to check the output of each layer.</param>
/// <returns>The results from the output neurons.</returns>
public virtual INeuralData Compute(INeuralData input,
NeuralOutputHolder useHolder)
{
try
{
return logic.Compute(input, useHolder);
}
catch (IndexOutOfRangeException ex)
{
throw new NeuralNetworkError(
"Index exception: there was likely a mismatch between layer sizes, or the size of the input presented to the network.",
ex);
}
}